Deep Learning with TensorFlow by Giancarlo Zaccone & Md. Rezaul Karim & Ahmed Menshawy

Author:Giancarlo Zaccone & Md. Rezaul Karim & Ahmed Menshawy [Zaccone, Giancarlo]
Language: eng
Format: azw3
Publisher: Packt Publishing
Published: 2017-04-24T04:00:00+00:00

def loss(pred, label):

cross_entropy_loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=label))

tf.summary.scalar('Entropy', cross_entropy_loss) reg_losses = tf.add_n(tf.get_collection("losses"))

tf.scalar_summary('Reg_loss', reg_losses)

return cross_entropy_loss + REGULARIZATION * reg_losses

def train(loss, step):

return tf.train.AdamOptimizer(LEARNING_RATE).

minimize(loss, global_step=step)

def get_next_batch(images, labels, step):

offset = (step * BATCH_SIZE) % (images.shape[0] - BATCH_SIZE)

batch_images = images[offset: offset + BATCH_SIZE]

batch_labels = labels[offset:offset + BATCH_SIZE]

return batch_images, batch_labels

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